Ikhlak Ahmed

The paper develops a machine learning-based T1D risk model tailored to Middle Eastern populations, showing improved performance over existing models in this region.

The paper improves T2D risk prediction using ensemble learning with multi-trait polygenic risk scores in the Qatar Biobank cohort.

The paper examines how HLA class II gene diversity influences antibody responses to common pathogens in an Arab cohort, finding that heterozygosity and synergistic allele effects enhance immunity.

The Qatar Genome Program sequenced 6,045 individuals, identifying 88 million variants, including novel ones, and revealed genetic structure and disease-related markers in the Qatari population.

This study shows that circNFATc3 affects cancer cell proliferation, migration, and oxidative phosphorylation through gain and loss of function experiments.

The paper identifies genetic variants that control circular RNA expression by analyzing circRNA and genome sequence variation in lymphoblastoid cell lines from the 1000 Genomes Project.

This paper introduces AVA-seq, a method using next-generation sequencing to map protein-protein interactions with high resolution, demonstrating its application on human proteins.

This study compares 3D and 2D ovarian cancer models to show TGF-β induces EMT, invasion, and aggressiveness, with reversible effects using a TGF-β inhibitor.

The paper identifies four conserved genes in male date palms, supporting a two-mutation model for the evolution of dioecy from hermaphroditism.